I have a Rails 4.x application running on server A and MySQL on server B.
Using ab to do a load test of my API calls I notice that the MySQL server is showing CPU activity. So I go back to the code and check, but no SQL statements are triggered, to be sure I also deactivate all before filters, but still the MySQL server shows CPU load.
I went to MySQL and run
show processlist;
but that also shows no active SQL statements
Why would there be load on the DB server?
A Rails application initializes connection pools to the configured database on app load and also loads basic schema data for each ActiveModel defined to populate runtime mappings from the DB to instances of that model.
These connections/queries will happen as soon as you have loaded the application and running traffic.
If this is not what is responsible for the activity on your database server, you will need to use other tools to see what is responsible. For example, NewRelic's system monitoring tools are great for snapshotting CPU/memory usage over time correlated to what processes were running. This will help you rule out MySQL itself using resources vs. other things running on the DB server.
According to this article, storage engines like Innodb may have their own per thread and/or global memory allocations which is probably accounting for the CPU overhead. If this is a stock (non-tuned) MySql install, you're probably just seeing baseline CPU activity. The article mentions a number of places to look that might indicate areas that can be tuned to reduce this footprint.
Related
I want to test Node and Deno and try to redirect users via proxy to one MySQL DB.
How will it impact the database?
Can some timestamp conflicts via CRUD operations arise or does MySQL have some mechanism to cope with connections from multiple servers?
What about performance or memory footprint of the database in RAM? Will it be occupying the same amount of space as if there was only one server requesting the database to CRUD something?
What would happen if I added another server that will connect to the DB, for example, java or Go server?
It will virtually have no impact on the database other than having any other concurrent processes connecting to it.
This is not a deno issue but rather a database issue.
The exact same problems can happen even with your current single Node.js instance, because the nature of all systems these days is concurrent/parallel.
You might as well replace the Deno app with another Node.js instance, Java, etc. Or even your current Node.js app.
Data in a database can change once you loaded it to the client, and it is up to you to implement the code that will handle such scenarios.
The fact that MySQL is not "ACID" is neither negative nor relevant in and of itself because it is doesn't have context.
If you need complete absolute integrity on a registry make sure you lock it when you select it, but there will be a trade off.
I have been working on the server migration of a legacy ecommerce application using PHP 5.6.
The switch involved two Dedicated 32 servers from Linode.
One server is for NginX + PHP and the other is for MySQL only.
The legacy application leverages memcached.
After the switch, I can see a heavy internal traffic caused due to private inbound and outbound connections.
So far this element didn't cause any problem on performance.
However, I was under the impression that the queries would be cached on the local machine, and not on the remote.
Because if the query is cached on the remote host, it sill has to transmit the result set over the private network, instead of retrieving from RAM or the local SSD.
Am I assuming this wrong?
It may be that I am missing the point where the private inbound traffic is more beneficial for overall performance when compared to a local cache.
MySQL has a feature called the Query Cache, but this caches query result sets in the mysqld server process, not on the client. If you run the exact same query again after the result has been cached in the Query Cache, it will copy the result from the Query Cache and avoid the cost of running the query again. But this will not avoid the time to transfer the result across the network from mysqld to your PHP application.
Also keep in mind that the MySQL Query Cache is being deprecated and retired.
Alternatively, your application may store data from query results in memcached, but typically this would be done by the application code (I know there are UDF's to read and write memcached from MySQL triggers, but this is a bad idea).
If your memcached service is not on the same host as your PHP code, it would result in network transfer twice: Once when querying the data from MySQL the first time, then again transferring the data into memcached, then later every time you fetch the cached data out of memcached.
PHP also has some features to do in-memory caching, such as APCu. I don't have any experience with this, and it's not clear from a brief scan of the documentation where it stores cached data.
PHP is designed to be a "shared nothing" language. Every PHP request has its own data, and data doesn't normally last until the next request. This is why a cache is typically not kept in PHP memory. Applications rely on either memcached or the database itself, because those will hold data longer than a single PHP request.
If you have a fast enough network, it shouldn't be a high cost to fetch items out of a cache over a network. The performance architects at a past job of mine developed this wisdom:
"Remote memory is faster than local storage."
They meant that if the data is in RAM on a server, then reading it from RAM even with the additional overhead of transferring it across a network is usually better than reading the data from persistent (disk) storage on the local host.
We have a 2GB Digital Ocean server, and it is dedicated for a MySQL server of other two PHP servers. we are using Percona MySQL Server 5.6 on this server. We configured MySQL replication and these configuration is working fine
Our issue is sometime our site monitoring tools reporting that some of the URL hosted with this server is down (May be this is happening once in a week or two). When I am checking, I could see that Mysql Master server load is too much high (May be 35 - 40), so the MySQL server was not responded. # that I usually do a MySQl service restart, this restart cause to server load become normal and the sites started working after service restart.
This is a back-end MySQL database server of 20-25 PHP applications (WordPress, Drupal and some custom applications server).
Here are my questions,
Why this server load automatically goes down, after a spikes happens?
Is there any way in which database is causing issues? So that I can identify the application too.
How can I identify the root cause of this issues
Depending upon your working dataset, a 2GB server providing access for 20-25 PHP applications (WordPress, Drupal and some custom applications server) could be the issue.
For example, if you have a 1.4GB buffer pool (assuming all tables are InnnoDB) and 10GB of data, then your various applications could end up competing for resources, such as I/O, buffer pool pages, Adaptive Hash Index, query cache. They could also, assuming caching is used, be invalidating theit caches within a similar timeframe, thus sending expensive queries to the database.
Whilst a load of 50 is something that you would normally want to avoid, the load average is not something that you should concern yourself with if showing in isolation.
The use of the uninterruptible state has since grown in the Linux
kernel, and nowadays includes uninterruptible lock primitives. If the
load average is a measure of demand in terms of running and waiting
threads (and not strictly threads wanting hardware resources), then
they are still working the way we want them to.
http://www.brendangregg.com/blog/2017-08-08/linux-load-averages.html
If the issue is happening once per week then it is starting to sound like a batch process, or cache expiration issue - too much happening at once for the resources available.
The best thing to do is to monitor and look for the cause. Since you are already using Percona Server, using PMM should give you the perfect insight to find the cause, although it works with Oracle MySQL, MariaDB, Aurora, etc. You can try a demo to see the insights that you can gain:
https://pmmdemo.percona.com. The software is Open Source and free to use.
You can look in QAN to find the most expensive queries, whilst looking at Prometheus data to give an insight into the host itself. There are some recommendations to get the most from PMM, depending upon your flavour of MySQL.
I'm seeing a few of these errors during high load times:
mysql_connect() [<a
href='function.mysql-connect'>function.mysql-connect</a>]: [2002] Resource
temporarily unavailable (trying to connect via
unix:///var/lib/mysql/mysql.sock)
From what I can tell the mysql server isn't hitting its max connections limit, but there's something else stopping it from serving the query. What other limits would MySQL be hitting?
I'm running RHEL 6.2 64bit with MySQL 5.5.21
Let's assume your system is currently Unix-based (as given in your problem statement). If this is correct, here's the set of issues you may be running into:
You've run out of memory available to MySQL.
This is the most likely problem you're facing. Each connection in MySQL's connection pool requires memory to function, and if this resource is exhausted, no further connections can be made. Of course, the memory footprints and maximum packet sizes of various operations can be tuned in your equivalent to my.cnf if you discover this to be an issue.
Here's an additional thread that can help there, but you may also consider using simpler profiling tools like top to get a good ballpark estimate of what's going on.
You've run out of file descriptors available to your MySQL user account.
Another common issue: if you're trying to service requests that require file IO above the 1,024 boundary (by default), you will run into cases where the operation simply fails. This is because most systems specify a soft and hard limit on the number of open file descriptors each user can have available at one time, and walking over this threshold can cause problems.
This will usually have a series of glaringly obvious signs expressed in your log files. Check /var/log/messages and your comparable directories (for example, /var/log/mysql to see if you can find anything interesting.
You've run into a livelock or deadlock scenario where your thread is unsatisfiable.
Corollary to memory and file descriptor exhaustion, threads can time out if you've overstepped the computational load your system is capable of handling. It won't throw this error message, but this is something to watch out for in the future.
Your system is running out of PIDs available to fork.
Another common scenario: fork only has so many PIDs available for its use at any given time. If your system is simply overforked, it will cease to be able to service requests.
The easiest check for this is to see if any other services can connect through to the machine. For example, trying to SSH into the box and discovering that you cannot is a big clue.
An upstream proxy or connection manager has run out of resources and ceased servicing requests.
If you have any service layer between your client and MySQL, it bears inspecting to see if it has crashed, hung, or otherwise become unstable. The advice above applies.
Your port mapper has exhausted itself after 65,536 connections.
Unlikely, but again, a possible exhaustion case. Checking the trivial service connection as above is, ehm, also the best port of call here.
In short: this is a resource exhaustion scenario, inclusive of the server simply being "down". You're going to have to profile your system further to see what you're blocking on. All the error message gives us in this case is the fact the resource is unavailable to the client -- we'd need to see more information about the server to determine a more adequate remedy.
I still haven't found which limits it was hitting, but I did manage to work around the problem. There was a problem with our session table (in vbulletin) which uses the MEMORY engine. The indexes for this table were HASH and thus when vbulletin purged this table once an hour it would lock the table just long enough to hold up other queries and push mysql to the limit of its resources.
By changing the indexes to BTREE this allowed MySQL to delete the rows from the session table a lot quicker and avoid any limits there were reached previously. The errors only started when we upgraded our master db server to MySQL 5.5, so I'm guessing MEMORY tables are handled differently in the latest release.
See http://www.mysqlperformanceblog.com/2008/02/01/performance-gotcha-of-mysql-memory-tables/ for information on speed increases from using BTREE indexes over HASH For MEMORY.
Geez, this could be so many things. It could be that the socket buffer space is exhausted. It could be that mysql is not accepting connections as fast as they are coming in and the backlog limit is reached (though I'd expect that to give you a "Connection Refused" error, I don't know for sure that's what you'll get for a Unix domain socket). It could be any of the things #MrGomez pointed out.
Since you are running Apache and MySQL on the same server and this is a problem under high load, it could well be that Apache is starving the system of some resource and you're just not seeing (noticing?) the dropped/failed incoming connections/requests in your logs.
Are you using connection pooling? If not, I'd start there.
I'd also look for errors in the Apache logs and syslog around the same time as the mysql_connect error and see what else turns up. I'd especially recommend getting MySQL moved over to its own separate dedicated server.
In my case, I was working with JSON data types with PDO (PHP Driver).
I was using fetch to retrieve one item but forgot to add LIMIT 1 to the query. Adding it solved the problem.
I am writing a db logging ruby gem which will simply take out a job from a Beanstalk queue and write it in the DB.
That is one process on Server A puts a job (that it wants to log) in the Beanstalk queue on Server B, and my logging process on Server B takes it out and writes it to the mysql DB on Server B.
I want to know if this is worth it?
Is putting a job in the Beanstalk queue faster than writing to the DB. Or can my process that wants to log to DB directly write it to DB instead of using the logging process.
Note that both the beanstalk server and DB are on another server.
Beanstalk internally makes a socket call from Server A to Server B.
I believe mysql would need to do the same as well?
So therefore is mysql to another server going to be slower than putting in the beanstalk queue.
It'll be much faster, primarily because Beanstalkd jobs, by default, are stored in-memory and are lost if, for example, you lose power on your server, whereas MySQL is a strongly ACID-compliant relational database, and hence will go to a lot of effort and flush each of your logs to disk.
I think you'll find that, after your do some benchmarking with a lot of logs being made by your system, that disk I/O will be your limiting factor, rather than the speed of TCP/IP sockets. Your current system's advantage is that when server A files a log on Server B's beanstalkd instance it takes up very little of Server A's time, and Server B can periodically flush our many logs at once from beanstalkd to MySQL, making the process more efficient. The disadvantage is that, the more you batch up the logs, the more logs you will lose in the event of a software / power failure, unless you use beanstalkd's "-b" parameter which makes jobs durable by writing them to disk (and hence making the process slower).
Of course, the only way to truly settle this question is to benchmark!